GNSOFT

AI Project Life Cycle

Using various technologies and knowledge such as data collection, data analysis, deep learning/machine learning, and distributed computing technologies.
It is the process of developing and visualizing suitable AI models and producing them as research/business products and services.

• Management functions : Distributed algorithm learning and job/resource management, and learning/inference data storage management
  • Data preprocessing : Data processing for learning, including data collection, verification, preprocessing, and amplification
  • Model Learning : Implement algorithms with DL/ML frameworks(TensorFlow, PyTorch, Caffe, Mxnet, etc)
  • Model management : DL/ML model evaluation, selection, and learned DL/ML model Lifecycle management, deployment, and re-learning management
  • Model inference : DL/ML Model Inference Services (Speed, Simultaneous, Resource Efficiency)
• Application Services